Heterogeneous consumer preferences for alternative fuel cars in China

This paper models consumer preferences for alternative fuel cars and conventional, petrol fueled cars in China. It compares discrete choice model specifications where each specification reflects how consumers choose between alternative fuel cars and conventional types of cars. We find that, in China, consumers differentiate between the types of alternative fuel cars and are more likely to consider switching from petrol fuel vehicles to hybrid than to electric cars. Segmentation analysis is used to explore groups of consumers and their likelihood of adopting alternative fuel cars.     

A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands

This paper presents results of an online stated choice experiment on preferences of Dutch private car owners for alternative fuel vehicles (AFVs) and their characteristics. Results show that negative preferences for alternative fuel vehicles are large, especially for the electric and fuel cell car, mostly as a result of their limited driving range and considerable refueling times. Preference for AFVs increases considerably with improvements on driving range, refueling time and fuel availability. Negative AFV preferences remain, however, also with substantial improvements in AFV characteristics; the remaining willingness to accept is on average € 10,000–€ 20,000 per AFV. Results from a mixed logit model show that consumer preferences for AFVs and AFV characteristics are heterogeneous to a large extent, in particular for the electric car, additional detour time and fuel time for the electric and fuel cell car. An interaction model reveals that annual mileage is by far the most important factor that determines heterogeneity in preferences for the electric and fuel cell car. When annual mileage increases, the preference for electric and fuel cell cars decreases substantially, whilst the willingness to pay for driving range increases substantially. Other variables such as using the car for holidays abroad and the daily commute also appear to be relevant for car choice.     

A network wide simulation strategy of alternative fuel vehicles

This paper presents an integrated simulator “CUIntegration” to evaluate routing strategies based on energy and/or traffic measures of effectiveness for any Alternative Fuel Vehicles (AFVs). The CUIntegration can integrate vehicle models of conventional vehicles as well as AFVs developed with MATLAB-Simulink, and a roadway network model developed with traffic microscopic simulation software VISSIM. The architecture of this simulator is discussed in this paper along with a case study in which the simulator was utilized for evaluating a routing strategy for Plug-in Hybrid Electric Vehicles (PHEVs) and Electric Vehicles (EVs). The authors developed a route optimization algorithm to guide an AFV based on that AFV driver’s choice, which included; finding a route with minimum (1) travel time, (2) energy consumption or (3) a combination of both. The Application Programming Interface (API) was developed using Visual Basic to simulate the vehicle models/algorithms developed in MATLAB and direct vehicles in a roadway network model developed in VISSIM accordingly. The case study included a section of Interstate 83 in Baltimore, Maryland, which was modeled, calibrated and validated. The authors considered a worst-case scenario with an incident on the main route blocking all lanes for 30 min. The PHEVs and EVs were represented by integrating the MATLAB-Simulink vehicle models with the traffic simulator. The CUIntegration successfully combined vehicle models with a roadway traffic network model to support a routing strategy for PHEVs and EVs. Simulation experiments with CUIntegration revealed that routing of PHEVs resulted in cost savings of about 29% when optimized for the energy consumption, and for the same optimization objective, routing of EVs resulted in about 64% savings.     

Forecasting petrol demand and assessing the impact of selective strategies to reduce fuel consumption

Abstract

The use of fossil fuels in transportation is an important topic as a result of growing concerns over global warming. Automobile petrol demand has been of particular interest to researchers and policy-makers, given that the automobile is a major contributor to the enhanced greenhouse effect. This paper forecasts Australia's automobile petrol demand up to the year 2020 based on the best performing forecasting model selected out of eight models. In order to establish ways to reduce the demand for petrol, and the consequent by-product of reducing the amount of greenhouse gas emissions, we have estimated the impact on CO₂ for several potential policy instruments, using Transportation and Environment Strategy Impact Simulator (an integrated transport, land use and environmental strategy impact simulation programme). We find that a carbon tax of AU$0.50/kg can reduce automobile kilometres by 5.9%, resulting in reduced demand for petrol and a reduction in CO₂ of 1.5%.     

An integrated modeling approach for facilitating emission estimations of alternative fueled vehicles

This paper develops an integrated model for reliable estimation of daily vehicle fuel savings and emissions using an integrated traffic emission modeling approach created by incorporating the US Environmental Protection Agency’s vehicle emission model, MOVES, and the PARAMICS microscopic traffic simulation package. A case study is conducted to validate the model using a well-calibrated road network in Greenville, South Carolina. For each transportation fuel considered, both emission and fuel consumption impacts are evaluated based on market shares.     

The impact of high-speed technology on railway demand

This paper estimates a passenger railway demand function to analyse effects arising from the introduction and use of high-speed technologies. The paper reports estimates of demand elasticities with respect to price, income, quality of service and a range of exogenous characteristics. The results show that travel time savings from conventional high-speed technology have a larger impact on passenger demand than tilting train technology. The introduction of conventional high-speed technology is associated with an 8% increase in passenger railway demand. Increasing the use of either type of high-speed technology appears to induce small positive effects on demand beyond those obtained from usual traffic density increases on non-high-speed existing technology.

风帆助航对船舶主机油耗率的影响

加装风帆是船舶节能的有效途径,但风帆助航会影响船舶主机和其他系统的运行状况,对船舶能效的影响主要来自主机工况的改变。本文通过分析加装风帆后对螺旋桨工作特性的影响,推导出了计算主机油耗率的方法,并使用某超大型油轮(VLCC)的相关参数进行验证计算,证明此方法简单实用,可为计算风帆助航船舶能效指数EEOI等相关参数提供参考。     

How much disruption to activities could fuel shortages cause? – The British fuel crisis of September 2000

In September of 2000 the UK experienced a blockade of oil refineries in response to rising fuel prices. These protests resulted in severe fuel supply disruptions that intensified over the course of about one week. During the peak of the crisis, travel activity by car was curtailed. This paper analyzes survey data collected about two months after the crisis utilizing the recent memory of respondents as to how they would expect this sort of disruption to affect their participation in daily activities. Specifically, we focused on a variety of non-discretionary and discretionary activities and examined what factors are associated with respondents expecting disruption to those activities. Statistical models were developed to analyze how demographic factors, commute mode selection, vehicle characteristics, and various other factors can explain how individuals expect disruption to their activities. Results suggest that the majority of individuals do not expect major disruptions, although for more car-dependent individuals, disruption was expected to be substantial, especially for work-related trips. These results have implications for the potential success and benefits of an integrated transport policy.     

影响营运客车燃料消耗量测量结果准确性的因素

结合JT711-2008营运客车燃料消耗的测量方法,阐述了影响营运客车燃料消耗测量的因素。     

The impact of car specifications,prices and incentives for battery electric vehicles in Norway: Choices of heterogeneous consumers

Electric vehicles (EVs), specifically Battery EVs (BEVs), can offer significant energy and emission savings over internal combustion engine vehicles. Norway has a long history of research and government incentives for BEVs. The BEV market in Norway allows us to fully examine consumers’ BEV choices influenced by car specifications, prices and government incentives (public bus lanes access, toll waiver and charging stations). The Random-Coefficient Discrete Choice Model (referred to as the BLP model) is applied to understand the choices of heterogeneous personal consumers and business buyers. Our study is instantiated on the entire EV sales data in Norway from 2011 to 2013, as well as a set of demographics at the municipality level. The results suggest significant positive effects of BEV technology improvement, space, toll waiver and charging station density on EV demand for both personal consumers and business buyers. However, the effects on business buyers may be generally less pronounced than on personal consumers. Interestingly, bus lanes access demonstrates a negative impact for personal consumers, possibly due to consumers’ concern regarding bus lane congestion. In addition, preferences on the BEV price can vary statistically among consumers with different income levels. Compared to the BEV technology development, demographical features and municipal incentives may have generally less impacts on market shares within the BEV market.     

The impact of urban form on automobile travel: disentangling causation from correlation

A longstanding question within the field of transportation demand management is the strength of the relationship between urban form and mobility behavior. Although several studies have identified a strong correlation between these variables, there is as yet scant evidence to support policy interventions that target land use as a means of influencing travel. To the contrary, some of the more recent research has cast skepticism on the proposition that the relationship is causative, recognizing the possibility that households endogenously self-select themselves into communities that support their preferences for particular transportation modes. Focusing on individual automobile travel, the present study seeks to contribute to this line of inquiry by estimating econometric models on a panel of travel-diary data collected in Germany between 1996 and 2003. Specifically, we employ the two-part model (2PM)—a procedure involving probit and OLS estimators—to assess the determinants of the discrete decision to use the car and the continuous decision of distance traveled. Beyond modeling variables that capture the urban form features that are commonly suggested to influence mobility behavior, including mixed use and public transit, this study employs instrumental variables to control for potential endogeneity emerging from the simultaneity of residential and mode choices. Unlike much of the work to date, our results suggest that urban form has a causative impact on car use, a finding that is robust to alternative econometric specifications.

The impact of strategic management and fleet planning on airline efficiency - A random effects Tobit model based on DEA efficiency scores

As a result of the liberalisation of airline markets; the strong growth of low cost carriers; the high volatility in fuel prices; and the recent global financial crisis, the cost pressure that airlines face is very substantial. In order to survive in these very competitive environments, information on what factors impact on costs and efficiency of airlines is crucial in guiding strategic change. To evaluate key determinants of 58 passenger airlines’ efficiency, this paper applies a two-stage Data Envelopment Analysis (DEA) approach, with partially bootstrapped random effects Tobit regressions in the second stage. Our results suggest that the effects of route optimisation, in the sense of average stage length of the fleet, are limited to airline technical efficiency. We show that airline size and key fleet mix characteristics, such as aircraft size and number of different aircraft families in the fleet, are more relevant to successful cost management of airlines since they have significant impacts on all three types of airline efficiency: technical, allocative and, ultimately, cost efficiency. Our results also show that despite the fuel saving benefits of younger aircraft, the age of an airline’s fleet has no significant impact on its technical efficiency, but does have a positive impact on its allocative and cost efficiency.